Journal of Sports Sciences

ISSN: 0264-0414 (Print) 1466-447X (Online) Journal homepage: http://www.tandfonline.com/loi/rjsp20

Do weight categories prevent athletes from relative age effect?
Nicolas Delorme
To cite this article: Nicolas Delorme (2014) Do weight categories prevent athletes from relative age effect?, Journal of Sports Sciences, 32:1, 16-21, DOI: 10.1080/02640414.2013.809470
To link to this article: http://dx.doi.org/10.1080/02640414.2013.809470

Published online: 24 Jul 2013.

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Date: 31 May 2016, At: 04:05

Journal of Sports Sciences, 2014
Vol. 32, No. 1, 16–21, http://dx.doi.org/10.1080/02640414.2013.809470

Do weight categories prevent athletes from relative age effect?

NICOLAS DELORME
University of Bordeaux, Laboratoire Cultures, Education, Sociétés, Bordeaux, France

Downloaded by [Universiteit Leiden / LUMC] at 04:05 31 May 2016

(Accepted 24 May 2013)

Abstract
The aim of this study was to investigate whether weight categories prevent young athletes from being exposed to a relative age effect. The dates of birth of all French female (n = 727) and male (n = 5440) amateur boxers who participated in the
2010–2011 season were collected from the federation database. The dates of birth of all French male professional boxers
(n = 354) were also collected. The results show an absence of a relative age effect among French female and male amateur boxers. The results also show an absence of this phenomenon among French male professional boxers. The male 18–18+ age category reveal an inverse relative age effect. This inverse relative age effect might be interpreted as the result of a strategic adaptation from relatively younger children who shift from one sport to another where there are weight categories in order to ensure fair competition. The results of this study suggest that the weight category system is a possible solution within the relative age effect phenomenon.
Keywords: relative age effect, weight categories, boxing, discrimination

In order to ensure fair sports competition, young athletes are often grouped into categories according to their chronological age. However, the current definition of age categories often results in a relative age effect (RAE). According to Cobley, Baker,
Wattie, and McKenna (2009, p. 235) this phenomenon refers ‘both to the immediate participation and long-term attainment constraints in sport, occurring as a result of chronological age and associated physical (e.g. height) differences as well as selection practices in annual age-grouped cohorts’. As a result, in one-year competition bands, two children in the same category may differ in age by as much as 12 months. The variation among teammates in terms of physical development (e.g. Carling, Le Gall, Reilly,
& Williams, 2009), especially during puberty (e.g.
Delorme & Raspaud, 2009a), is thus likely to be considerable. On average, the relatively older players possess significant assets in terms of their size, weight, and strength, which influence their ‘perceived potential’ (Carling et al., 2009; Helsen, Van
Winckel, & Williams, 2005). These adolescents are more easily identified as ‘talented’ and are thus more apt to be selected for professional training or for national teams, which obviously gives them a better chance of reaching a high level of play or professional careers. This has been consistently illustrated by the unbalanced distribution of birthdates among elite

players: players born at the beginning of the competition year are typically over-represented, whereas those born at the end of the year are underrepresented (e.g. Delorme, Boiché, & Raspaud,
2009; Musch & Hay, 1999; Pérez Jiménez & Pain,
2008). This unequal distribution has also been noted in young elite athletes (e.g. Barnsley & Thompson,
1988; Helsen et al., 2005; Williams, 2010).
Conversely, in activities such as dance and gymnastics, where physical attributes are not important, or even possibly disadvantageous, the RAE does not operate (e.g. Van Rossum, 2006).
However, a RAE is observed not only in elite youth and adult athletes. Delorme and Raspaud
(2009a) demonstrated this effect in the entire population of young players registered in the French
Basketball Federation. A systematic RAE was also detected in the whole population of French female soccer players (Delorme, Boiché, & Raspaud,
2010b) and Swiss female soccer players (Romann
& Fuchslocher, 2011). Two complementary hypotheses (as yet unproven) may explain this unbalanced distribution at the amateur level. First, relatively younger children may be dissuaded from participating in sports that require certain physical attributes because they are developmentally at a disadvantage compared with relatively older children (Delorme,
Boiché, & Raspaud, 2010a; Delorme, Boiché, &

Correspondence: Nicolas Delorme, University of Bordeaux, Laboratoire Cultures, Education, Sociétés, Bordeaux, France. Email: nico_delorme@hotmail.com
© 2013 Taylor & Francis

Downloaded by [Universiteit Leiden / LUMC] at 04:05 31 May 2016

RAE and weight categories
Raspaud, 2010c; Delorme, Chalabaev, & Raspaud,
2011). Second, those relatively younger children who participate anyway are more prone to drop out
(Delorme et al., 2010a; Delorme et al., 2011;
Helsen, Starkes, & Van Winckel, 1998).
Some authors even qualify RAEs as discriminatory
(e.g. Edgar & O’Donoghue, 2005; Hurley, Lior &
Tracze, 2001; Musch & Hay, 1999). For these authors, even if the discrimination is inadvertent, it needs to be cautiously examined, given the lucrative nature of certain sports. Others argue that sports are health-enhancing and should enable every child to blossom (e.g. Musch & Grondin, 2001). The selection system thus works against societal goals such as inclusion, availability, the right for every individual to develop his/her unique capacities within sports, and policies to promote physical activity for all children and youth. Indeed, the system seems detrimental for certain children’s motivation, leading them to drop out and perhaps curtailing the physical activity habits they ideally would carry into adulthood.
Fortunately, recent findings suggest that RAE does not influence physical activity level in adults
(Larouche, Laurencelle, Grondin, & Trudeau,
2010). More pragmatically, some authors note that
RAE, as an artificial consequence of the youth competition structure, generates a loss in potentially talented players, which in the long run contributes to a decrease in the level of professional and national teams (e.g. Pérez Jiménez & Pain, 2008).
Given these potential economic, psychological and health-related outcomes of RAE, the majority of authors agree that this phenomenon needs to be reduced or eliminated. New categorisation systems have thus been proposed for young sports participants, based on either biological (e.g. Baxter-Jones,
1995) or chronological age (e.g. Hurley, 2009;
Hurley et al., 2001), in order to deal with the negative correlates of relative age differences. Such suggestions are nevertheless difficult to apply, given the limited number of players in small teams/clubs.
However, in addition to age categories, in some sports young athletes are also grouped into weight categories (e.g. judo, boxing, weightlifting, wrestling). Weight categories are mainly present among fighting sports in order to ensure fair competition.
The aim of this study is thus to investigate whether weight categories reduce or eliminate a RAE in young athletes. Indeed, as discussed previously, the relatively older players possess significant assets in terms of their size, weight, and strength, which influence their ‘perceived potential’ (e.g. Carling et al.,
2009; Helsen et al., 2005). For instance, in their study focusing on under-14 youth academy soccer players, Carling et al. (2009) found significant differences in body mass (≈ 7 kg) between early-born and late-born players. Sherar, Baxter-Jones, Faulkner,

17

and Russell (2007) examined the relationships among biological maturity, physical size, relative age and selection into a male Canadian provincial age-banded ice hockey team (14–15 years old category). They found that ‘the ice hockey players selected for the final team were taller, heavier, and more mature (P< 0.05) than both the unselected players and the age-matched controls’ (Sherar et al., 2007, p. 879). They also found that the majority of selected players were born at the beginning of the competitive year and concluded that ‘team selectors appear to preferentially select early maturing male ice hockey players who have birth dates early in the selection year’ (Sherar et al., 2007, p. 879).
Furthermore, because of the disadvantages that result from relative age (i.e. less advanced physical development), it is assumed that young players born late in the competitive year experience greater failure and inferiority in their practice, and may be disadvantaged by less playing time during official events.
Indeed, during adolescence, physical performance is correlated with biological maturation (e.g.
Philippaerts et al., 2006). For instance, Vaeyens,
Philippaerts, and Malina (2005) demonstrated that players born early in the competitive year received more opportunities to play than their late-born counterparts. Because of this less positive experience, it is likely that young players born later in the year will feel less competent in the activity and may ultimately drop out (Delorme et al., 2010a; Delorme et al.,
2011; Helsen et al., 1998) or participate in sports in which physical attributes – such as weight – are less important and/or inoperative (e.g. Delorme &
Raspaud, 2009b; Larouche et al., 2010).
To sum up, relatively younger children may be dissuaded from participating in sports that require certain physical attributes because they are developmentally at a disadvantage compared with relatively older children. The existence of weight categories may counterbalance this negative feeling, help to reduce maturational differences, and eliminate or reduce a RAE. Indeed, with a weight category system, the advantages that result from relative age (i.e. more advanced physical development) no longer exist. Children are grouped according to their chronological age but also according to their physical attributes (i.e. weight).
In order to test this hypothesis, data from the
French Boxing Federation (FBF) were analysed.
First, the distributions of the dates of birth of all registered amateur boxers were examined. As RAE decreases with increasing age (e.g. Musch &
Grondin, 2001, van den Honert, 2012), each age category was analysed separately. Then the same analysis was conducted among all registered professional boxers in order to investigate whether the detection/selection system discriminates against

18

N. Delorme

children born late in the competitive year regardless of weight categories. For both samples, an absence of RAE is expected.

distributions were calculated for the corresponding years for the French male and female populations.
Data were provided by the National Institute of
Statistics and Economics Studies (INSEE). Odds ratio (OR) analyses were also performed in order to determine the effect size of RAEs. OR and 95% confidence intervals (CI) were calculated by comparing quarters to Q4 (i.e. Q1 versus Q4, Q2 versus Q4, Q3 versus Q4). These procedures are effective in showing participation inequalities and the effect size of RAEs
(Cobley et al., 2009; Till et al., 2010, van den Honert,
2012). These tests were used to identify where RAEs became established. The calculations were carried out with the software Statistica version 6.1 (StatSoft Inc.).
For all tests, statistical significance was set at P < 0.05.

Methodology

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Data collection
The FBF includes four age categories (12–13, 14–
15, 16–17 and 18–18+). Each age category includes several specific weight categories (see Table I). The dates of birth of all female (n = 727) and male (n =
5440) amateur boxers who participated in the 2010–
2011 FBF season were collected from the federation database. Female and male boxers without French citizenship were excluded in order to control the cutoff dates. 12–13 female boxers (n = 19) were excluded due to the small sample sizes, which precluded reliable statistics.
The dates of birth of all male professional boxers
(n = 354) were also collected from the FBF database. Female professional boxers (n = 20) were excluded due to the small sample size, which precluded reliable statistics. Professional male boxers without French citizenship were excluded in order to control the cut-off dates.

Results
Female boxers
Table II shows the distributions by quarters of female boxers. For the 14–15 age category, a significant uneven distribution – that is however not typical of RAE – was found (χ2 = 7.95, df = 3, P < 0.05). An analysis by half-year revealed a uniform distribution between early-born and late-born female boxers
(χ2 = 0.09, df = 1, P < 0.77). Furthermore, no significant ORs were found in this age category.
For the 16–17 age category, a statistically significant
RAE was not observed (χ2 = 1.33, df = 3, P < 0.72).
The 18–18+ age category also showed a skewed distribution that is not typical of RAE (χ2 = 9.44, df = 3, P < 0.02). An analysis by half-year revealed a uniform distribution between early-born and lateborn female boxers (χ2 = 3.50, df = 1, P < 0.07).
No significant ORs were found in this age category.

Data analysis
The cut-off date in the French boxing system is 1
January. Thus, the birth months of boxers were classified in four quarters beginning with the January–March period (Q1) and finishing with the October–December period (Q4). Next, a chi-square goodness-of-fit test was conducted to determine whether the observed distribution per quarter significantly differs from the expected theoretical distribution. Expected birth date

Male boxers
Table I. Weight categories according to sex and age categories
Age category

Females

Males

13
13
13
18

18–18+
16–17
14–15
12–13

Table III shows the distribution by quarters of male boxers. No significant uneven distributions were found for male boxers in the 12–13 (χ2 = 4.83, df
= 3, P < 0.18) and 16–17 (χ2 = 1.89, df = 3, P <
0.60) age categories. For the 14–15 age category, a significant uneven distribution – that is however not typical of RAE – was found (χ2 = 8.03, df = 3, P <

11
11
14
18

Table II. Distribution of French female boxers (2010–2011)
Age category

Q1

Q2

Q3

Q4

Total

χ2

P

OR (CI) Q1 vs Q4

OR (CI) Q2 vs Q4

OR (CI) Q3 vs Q4

14–15
(Δ)
16–17
(Δ)
18–18+
(Δ)

38
(+8)
45
(+5)
87
(–5)

25
(–7)
38
(–5)
125
(+24)

39
(+8)
45
(+2)
90
(–20)

22
(–9)
40
(–2)
114
(+1)

124

7.95